How I Tracked Down the Top 4 HABs in the US.
Part 1 of 3
HAB research is messy. This blog post is part research journal, part explainer, and part cautionary tale — perfect for anyone who wants to know what’s really behind the green gunk in your favorite lake.
Figure 1: NOAA map of U.S. regions affected by different HAB types
How I did my HAB research (and what went wrong)
If you’ve read any headlines about harmful algal blooms (HABs) lately, chances are they mention one of the “Big Four” — Cyanobacteria, Karenia brevis, Pseudo-nitzschia, or Alexandrium catenella. Together, these species account for roughly 90% of the most disruptive blooms across the U.S.
Before you doubt this claim, let me explain.
When I began my research journey, I was struck by a simple question: With so many different types of algae, how do we decide which blooms are the most important or the most dangerous? I needed a way to compare them — an “apples-to-apples” measure of impact.
My first thought was economic loss. The greater the financial damage, the higher the importance. A straightforward assumption.
Like everyone these days, I turned to AI to aid me in the process. But all the chatbots only gave me made-up numbers. Dead end. I was frustrated; I spent all those hours for nothing. But wait, why was I getting false numbers in the first place? I thought about it strongly. Was AI generating random answers simply because there wasn’t reliable data? Or was I asking the wrong question altogether?
I shifted my focus: instead of chasing a single economic value, I started asking what actually drives those economic impacts.
As I dug deeper, I noticed something interesting, every study quantified HAB impacts differently. Some focused on lost tourism revenue, others on lost wages, healthcare costs, or shellfish contamination affecting local businesses. Each paper reflected what mattered most to that particular region.
For example, Florida-based research emphasized the 2017 Karenia brevis bloom’s toll on tourism—a natural focus for a state that thrives on visitors.
That’s when it clicked. Blooms aren’t predictable time-series events; they’re sporadic and uncertain. No amount of research can perfectly predict where, when, or how damaging a HAB will be. Each bloom is unique, with its own set of consequences which meant classifying them by region didn’t make sense either.
And that realization led me to a key insight: the frequency of bloom occurrence itself is a major driver of perceived economic impact. The more blooms happen, the more papers are written, and the greater the documented economic losses appear to be.
The top 4 HABs that affect 90% of the U.S.
NOAA (National Oceanic and Atmospheric Administration) was a great, trustworthy source. They’ve confidently published many articles marking down regions that witnessed specific algae blooms. They did the groundwork; now I needed to add some numbers to it. Here’s how I did it:
NOAA has identified four regions where HABs are a critical problem to federal, state, and local managers:
- Florida, Eastern Gulf, Western Gulf (Karenia brevis + Cyanobacteria microcystin)
- Lake Erie (Cyanobacteria)
- Gulf of Maine (Alexandrium fundyense)
- Washington Coast (Pseudo-nitzschia) (NCCOS, 2017)
Figure 2: My conclusion on the top 4 HABs in the US
Using NOAA’s research articles and their frequency over the past 30 years, I narrowed down the top four important ones with their specific regions. Click on the next article to understand my conclusions.
In an upcoming article, we’ll explore the Top 2 HABs that impact 90% of the U.S., where they occur, and the damage they’ve done.
Stay tuned!
References:
- (NCCOS, 2017)
National Centers for Coastal Ocean Science. (2017). Harmful algal bloom (HAB) forecasting. NCCOS – National Centers for Coastal Ocean Science. https://coastalscience.noaa.gov/project/harmful-algal-bloom-hab-forecasting/